Triple

T11086366
Position Surface form Disambiguated ID Type / Status
Subject Bahr el Ghazal E262129 entity
Predicate contains P35 FINISHED
Object Wau E904022 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wau | Statement: [Bahr el Ghazal, contains, Wau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wau
Context triple: [Bahr el Ghazal, contains, Wau]
  • A. Wau chosen
    Wau is a major city in northwestern South Sudan that serves as an important administrative, commercial, and transport hub.
  • B. Wau
    Wau is a town in Papua New Guinea historically notable as the site of a significant World War II battle between Allied and Japanese forces.
  • C. Wana
    Wana is a town in Pakistan’s Khyber Pakhtunkhwa province that serves as a key administrative and commercial center in the South Waziristan region.
  • D. Ouakam
    Ouakam is a coastal district of Dakar, Senegal, known for its historic fishing community, military installations, and prominent location beneath the African Renaissance Monument.
  • E. Waiyana
    Waiyana is an alternative name for the Wayana language, an indigenous Cariban language spoken by the Wayana people in parts of Brazil, Suriname, and French Guiana.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d799c3ed9c8190a3f5cdf1fe0e74a2 completed April 9, 2026, 12:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69e42d66ded88190877a20a10f012d6b completed April 19, 2026, 1:18 a.m.
Created at: April 8, 2026, 9:27 p.m.